Distribution of hospital beds in Tehran Province based on Gini coefficient and Lorenz curve from 2010 to 2012

The impact of the Iranian health transformation plan policy on equitable access to medical imaging services in West Iran

OBJECTIVE

Equity in the delivery of health services, including diagnostic imaging, is crucial to achieving universal health coverage. The Health Transformation Plan (HTP), launched in 2014, represents a major healthcare policy to improve the quality and accessibility of healthcare services. This study aimed to explore the impact of the HTP on equity in the access to medical imaging in Lorestan province, located in west Iran, from 2014 to 2023. Annual growth rates (AGR) of imaging devices were calculated, whilst equity assessment of medical imaging distribution was carried out by means of the Gini coefficient and the Lorenz curve per 100,000 population. The latter was generated using the cumulative distribution of imaging devices, as well as the cumulative population ratio.

RESULTS

Between 2014 and 2023, the number of imaging devices has increased threefold. The AGR of installing CT and MRI scanners in Lorestan province increased between 2014 and 2023. The Gini coefficients increased from 0.12 for CT and 0.16 for MRI in 2014 to 0.33 in 2023 for both devices. This indicates a decrease in equity in access to these fundamental health technologies despite the increase in their figures. Policymakers should better allocate medical equipment based on the specific health needs of different regions throughout Iran.

The allocation and fairness of health human resources in Chinese maternal and child health care institutions: a nationwide longitudinal study

BACKGROUND

In response to an aging population, the Chinese government implemented the three-child policy in 2021 based on the comprehensive two-child policy. With the implementation of the new birth policy, people's maternal and child health (MCH) needs will also increase. The allocation and fairness of MCH human resources directly affect people's access to MCH services. The purpose of this study is to analyze the allocation of health human resources in Chinese maternal and child health care institutions, evaluate the fairness of the allocation, to provide a reference for the rational allocation of MCH human resources.

METHODS

The data of health technicians, licensed (assistant) physicians, and registered nurses in maternal and child health care institutions nationwide from 2016 to 2020 were included. The health resource density index (HRDI) is used to evaluate the allocation level of MCH human resources. The Gini coefficient (G) and Theil index (T) are used to evaluate the fairness of the allocation of MCH human resources from the perspectives of population and geographic area.

RESULTS

From 2016 to 2020, the average annual growth rate of the number of health technicians, licensed (assistant) physicians, and registered nurses in Chinese maternal and child health care institutions was 7.53, 6.88, and 9.12%, respectively. The Gini coefficient (G) of the three types of MCH human resources allocated by population were all below 0.23, and the Gini coefficient (G) allocated by geographical area were all above 0.65. The Theil index (T) of the three types of MCH human resources allocated by population was all lower than 0.06, and the Theil index (T) allocated by geographical area was all higher than 0.53. In addition, the three types of MCH human resources allocated by population and geographic area contributed more than 84% of the Theil index within the group (T_intra) to the Theil index (T).

CONCLUSIONS

China's MCH human resources were fair in terms of population allocation, but unfair in terms of geographical area allocation. In the future, more attention should be paid to the geographical accessibility of MCH human resources, and the allocation of resources should comprehensively consider the two factors of serving the population and geographical area.

Analysis of medical resources for allocation equity using traditional Chinese medicine resource as a model

OBJECTIVES

This study is designed to analyse current allocation equity of medical resources in China for a better distribution of medical resources.

METHODS

Descriptive statistical methods were used to analyse the overall allocation of Traditional Chinese medicine (TCM) resources between 2012 and 2018. Lorentz curve and Gini coefficient were used to quantitatively analyse the fairness of the allocation from the population and geography two dimensions.

RESULTS

This study revealed an increase of TCM resources for the 6-year period, but the fair allocation of these resources was subjected to the methods used. The Gini coefficients were <0.3 based on population distribution but >0.5 basing on the geography allocation.

CONCLUSION

Population based analysis for the equity of the TCM resource allocation is superior, more attention for health resource planning is needed to focus on geographical fairness in the future, especially for the less populated rural regions.

Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China

Comprehensive investigation on understanding geographical inequalities of healthcare resources and their influencing factors in China remains scarce. This study aimed to explore both spatial and temporal heterogeneous impacts of various socioeconomic and environmental factors on healthcare resource inequalities at a fine-scale administrative county level. We collected data on county-level hospital beds per ten thousand people to represent healthcare resources, as well as data on 32 candidate socioeconomic and environmental covariates in southwest China from 2002 to 2011. We innovatively employed a cutting-edge local spatiotemporal regression, namely, a Bayesian spatiotemporally varying coefficients (STVC) model, to simultaneously detect spatial and temporal autocorrelated nonstationarity in healthcare-covariate relationships via estimating posterior space-coefficients (SC) within each county, as well as time-coefficients (TC) over ten years. Our findings reported that in addition to socioeconomic factors, environmental factors also had significant impacts on healthcare resources inequalities at both global and local space–time scales. Globally, the personal economy was identified as the most significant explanatory factor. However, the temporal impacts of personal economy demonstrated a gradual decline, while the impacts of the regional economy and government investment showed a constant growth from 2002 to 2011. Spatially, geographical clustered regions for both hospital bed distributions and various hospital bed-covariates relationships were detected. Finally, the first spatiotemporal series of complete county-level hospital bed inequality maps in southwest China was produced. This work is expected to provide evidence-based implications for future policy making procedures to improve healthcare equalities from a spatiotemporal perspective. The employed Bayesian STVC model provides frontier insights into investigating spatiotemporal heterogeneous variables relationships embedded in broader areas such as public health, environment, and earth sciences.

Inequality in distribution of burn facilities in Iran

Background: Inequality in the distribution of medical equipment and facilities has mainly been observed in health centers and, particularly, in governmental hospitals in each country. This study aimed to assess inequality in the distribution of burn facilities in Iran, including burn beds and specialist physicians needed for burn patients in 2017. Methods: This was a descriptive-analytic study, in which statistical records of the Ministry of Health and Medical Education for 2017 and the Population and Housing Report of 2016 of the Statistical Centre of Iran were used. The main variables studied were number of burn beds and number of general surgeons and plastic surgeons in medical universities in the provinces of Iran. Inequality in the distribution of these variables was evaluated using the Gini coefficient and the Lorenz curve. Excel 2010 software was used for data analysis. Results: In 55% of the provinces, the number of beds per capita for 100 000 population was lower than the average of Iran (1.26 beds of burn ward), and in 45% of the provinces, it was higher than the average of Iran in terms of this index. The results showed that burn beds were distributed unevenly in medical universities (G=0.42). However, the provincial distribution of these beds had a favorable condition (G=0.21). Also, the numerical value of the Gini coefficient showed the alert status in the distribution of specialist physicians based on the university distribution (G=0.51). Conclusion: Although solving the problems related to equality in the distribution of health resources is not an easy task, assessing this issue has a great impact on improving the policymaking procedures and allocating the health system resources. For the first time, this study presented some policies to avoid centralization and prevent some metropolitan cities from turning into cities with limited burn facilities through a comprehensive reviewing of the distribution of the main sources needed by the Iranian burn patients.

Inequalities in the geographic distribution of hospital beds and doctors in traditional Chinese medicine from 2004 to 2014

Objectives

This study identifies inequities in the provincial-level geographical distribution of traditional Chinese Medicine (TCM) hospital beds and doctors in China from 2004 to 2014. This provides policy implications of the optimal allocation of TCM health care resources.

Methods

Our study used province level data on TCM hospital beds and doctors from 2004 to 2014. These data were obtained from the China TCM Yearbook 2004–2014 and the China Statistical Yearbook 2004–2014.Global and local spatial autocorrelation was performed by using Moran’s index and the local Moran’s index to describe the spatial distribution of TCM hospital beds (doctors) as well as their density. A Gini coefficient was used to estimate inequalities in the geographic distribution of TCM hospital beds (doctors) based on their density. Correlations of the Gini coefficients between TCM hospital beds and doctors were calculated by Pearson correlation analysis.

Results

All indicators of TCM hospital beds and doctor density have increased over the past 11 years. The number of TCM hospital beds per 10,000 populations increased the fastest. Geographical clustering was not obvious in the density distribution of TCM hospital beds or doctors, as no significant spatial autocorrelation was found. Gini coefficients showed that from 2004 to 2014 the distribution of TCM hospital beds per 10,000 population and doctors per 10,000 populations were equitable between different regions. A large gap existed in the distribution inequality of TCM hospital beds (doctors) per square kilometer among different regions.

Conclusion

Targeted health policy with equitable distribution of TCM hospital beds (doctors) per square kilometer and the balance and coordination of related resources should be a priority in shaping China’s healthcare system reform.

Applying Gini coefficient to evaluate the author research domains associated with the ordering of author names: A bibliometric study

BACKGROUND

Team science research includes the number of coauthors in publications. Many papers have discussed the ordering of author names and the contributions of authors to a paper. However, no paper addresses the relation between authors' research domains and personal impact factors (PIF) with the ordering of author names. We aimed to apply Gini coefficient (GC) to evaluate the author research domains associated with the PIF and the ordering of author names on academic papers.

METHODS

By searching the PubMed database (Pubmed.com), we used the keyword "medicine" [journal] and downloaded 10,854 articles published from 1969 to 2018. A total number of 7502 articles labeled with complete author's countries/areas were included in data analysis. We also proposed a PIF index and jointly applied social network analysis (SNA), the GC, and Google Maps to report the following data with visual representations: the trend of author collaboration in Medicine; the dominant nations and keywords in Medicine; and the author research domains in Medicine associated with the PIF and the ordering of author names on academic papers.

RESULTS

The trend of author collaboration in Medicine is slightly declining (= -0.06) based on the number of authors per article. The mean number of individuals listed as authors in articles is 7.5. Most first authors are from China (3649, 48.64%) and Taiwan (847, 11.29%). The median of GC (0.32) and PIF (0.74) for the middle authors are obviously less than those for the first (0.53, 2.19) and the last authors (0.42, 2.61). A perfect positive linear relation with a large effect exists between GC and PIF because the correlation coefficient is 0.68 (>0.50, t = 2.48, n = 9).

CONCLUSION

Results suggest that the corresponding author is submitting the manuscript to the target journal with a core author's academic background and the personal impact factor related to the research domain and the journal scope in the future. As such, peer reviewers can quickly determine whether the manuscript is a potentially citable research paper.

The Lorenz curve: a novel method for understanding viral load distribution at the population level

Existing HIV care cascade metrics fail to capture whether viremia is equally distributed in a population or concentrated within groups. We applied the Lorenz curve, which has been used to describe disparities in the distribution of income and other resources, to the distribution of viremia in a safety-net HIV clinic in 2012. Among 1855 established clinic patients, 1% of the population held 50% of the virus and 10% of the population held 94% of virus.